{"id":"W4248763964","doi":"10.1515/iupac.79.0962","title":"Bystander Exposure","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemical Safety and Risk Management","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Toxicology; Hazard; Computer science; Chemistry; Philosophy; Biology; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002824281,0.0005535588,0.0006686127,0.0001087852,0.00007969518,0.0000370873,0.0006161116,0.0005898688,0.009588142],"category_scores_gemma":[0.000341451,0.0003900501,0.0002869547,0.0001781855,0.00009623136,0.00007374811,0.0003616161,0.00072305,0.00001340472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006161588,"about_ca_system_score_gemma":0.000131061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005183058,"about_ca_topic_score_gemma":0.00009190937,"domain_scores_codex":[0.9970472,0.0000264134,0.0005740085,0.0006101737,0.001142818,0.0005993806],"domain_scores_gemma":[0.9983015,0.0001205899,0.0001759091,0.0009581737,0.0001946388,0.0002491745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001194453,0.0001848318,8.742239e-7,0.0003370905,0.0001910728,0.00006295337,0.000004874873,0.00001943453,0.0002578742,0.00005713514,0.9960777,0.002686743],"study_design_scores_gemma":[0.001113652,0.0000612091,0.000002665321,0.000502649,0.000144182,0.00000570124,0.00001045766,0.00002798113,0.0003244171,0.00017653,0.9970323,0.0005982512],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000212837,0.001232737,0.00185253,0.0007281358,0.0006353286,0.000231197,0.994828,0.0002036684,0.0002671415],"genre_scores_gemma":[0.00005000372,0.001714618,0.00004751643,0.0002661732,0.001474212,0.00001955918,0.9940609,0.00006362595,0.002303389],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.009574737,"threshold_uncertainty_score":0.9998552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009881274915724802,"score_gpt":0.3427034210599531,"score_spread":0.3328221461442282,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}